This project is a Python application aimed at tracking attendance using computer vision. The project utilizes face recognition technology and user authentication. The main objective of the project is to take attendance in a specific class or event and save the attendance data to a CSV file.
- User Authentication: The project starts with username and password input. If the username and password are correct, access to the attendance-taking screen is granted.
- Face Recognition: Faces of participants are recognized using face recognition technology from images captured by the camera. Recognized participants are added to the attendance list.
- Attendance Taking: Names of recognized participants along with their entry time and date are saved to a CSV file.
- Interface: A simple user interface is created using the Tkinter library. The interface is designed to guide the user and provide information during the process.
- Python 3.x
- OpenCV
- NumPy
- Face Recognition
- Tkinter
- Pillow
You can install the required libraries using the following command:
pip install opencv-python numpy face_recognition pillow
- Run the main.py file to start the project.
- Fill in the username and password fields and click the "Login" button.
- In the attendance-taking screen, stand in front of the camera and wait for your face to be recognized.
- Upon successful face recognition, your name will appear on the screen and will be added to the attendance list.
- Press the ESC key to finish taking attendance.
- When editing project files, securely store sensitive information such as usernames and passwords in the main.py file.
- When editing project files, you can update the photos of individuals in the encodeListKnown variable to improve the recognition quality of the camera.